New energy frequency modulation energy efficiency improvement method and system based on frequency controller parameter optimization

Abstract

The invention relates to the technical field of new energy power supplies, in particular to a new energy frequency modulation energy efficiency improvement method and system based on frequency controller parameter optimization, and the method comprises the steps: building frequency response models of all types of new energy power supplies, and enabling the frequency response models to be built based on a unit model and a frequency controller model; according to the difference value between the output power reference value of the new energy power supply and the actual output, establishing an objective function of new energy frequency modulation energy efficiency optimization; and solving the objective function through a particle swarm algorithm, and optimizing the parameters of the frequency controller model of the new energy power supply. According to the method, the frequency response models of the new energy power supply and the traditional power supply are established, the output power variable quantity reference value of each power supply is accurately calculated, the parameters of the new energy frequency controller are optimized by adopting the particle swarm optimization, the limitation of the traditional experience setting method is overcome, and the optimized parameters are used for controlling; the energy efficiency of new energy frequency modulation is improved, and the frequency control effect of a power system is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy power supply technology, and in particular to a method and system for improving energy efficiency of new energy frequency modulation based on frequency controller parameter optimization. Background Art

[0002] With the rapid development of new energy generation technologies, the penetration of renewable energy sources such as wind power and photovoltaics in the power system continues to increase. However, the intermittent and fluctuating nature of new energy sources poses new challenges to the frequency stability of power systems. Traditional power systems primarily rely on the inertial response and primary frequency regulation capabilities of synchronous generators to maintain frequency stability. However, new energy generators are typically connected to the grid through power electronic equipment, which has weak inertial support and frequency regulation capabilities, resulting in a decrease in the system's frequency regulation capabilities.

[0003] Currently, the main methods for renewable energy to participate in frequency regulation include virtual inertia control, droop control, and additional frequency control strategies. However, existing methods often rely on experience or fixed patterns for parameter tuning, making them difficult to adapt to changing operating conditions. This leads to inefficient frequency regulation and may even cause secondary frequency fluctuations. Furthermore, the coordinated control of renewable energy and traditional power sources also faces optimization challenges. A method that can dynamically optimize frequency controller parameters is urgently needed to improve the efficiency of renewable energy frequency regulation. Summary of the Invention

[0004] (1) Purpose of the invention

[0005] The purpose of the present invention is to provide a method and system for improving the energy efficiency of renewable energy frequency modulation based on frequency controller parameter optimization, which improves the frequency control effect of the power system by optimizing the parameters of the frequency controller.

[0006] (2) Technical solution

[0007] To solve the above problems, the present invention provides a method for improving energy efficiency of new energy frequency modulation based on frequency controller parameter optimization, comprising:

[0008] Establishing frequency response models for each type of new energy power source, respectively, wherein the frequency response models are established based on a unit model of the new energy power source and a frequency controller model of the new energy power source;

[0009] Calculate the power system frequency deviation based on the output power change of new energy power sources, the output power change of traditional power sources and load demand;

[0010] Calculating a reference value of output power variation of the new energy power source based on the frequency response model;

[0011] Calculate the output power reference value of the new energy power source according to the output power variation reference value of the new energy power source;

[0012] According to the difference between the output power reference value and the actual output of the new energy power source, the objective function of the new energy frequency regulation energy efficiency optimization is established;

[0013] The objective function is solved by particle swarm optimization to optimize the frequency controller model parameters of the new energy power supply.

[0014] In another aspect of the present invention, preferably,

[0015] The unit model represents the relationship between the unit output power and the frequency control command, and simulates the dynamic response of the inverter through the first-order inertia link;

[0016] The frequency controller model includes inertia control and droop control.

[0017] In another aspect of the present invention, preferably, the new energy power source includes a wind turbine;

[0018] The frequency response model of the wind turbine generator system is expressed as:

[0019]

[0020] in, is the reference value of the output power variation of the wind turbine; are the inertia control coefficient and droop control coefficient of the wind turbine frequency controller, respectively, and Δf is the power system frequency deviation; represents the rate of change of power system frequency, T WF is the time constant of the wind turbine inverter, and s represents the differential operator.

[0021] In another aspect of the present invention, preferably, the new energy power source includes a photovoltaic unit;

[0022] The frequency response model of the photovoltaic system is expressed as:

[0023]

[0024] in, is the reference value of the output power variation of the photovoltaic unit; are the inertia control coefficient and droop control coefficient of the PV unit frequency controller respectively; Δf is the power system frequency deviation; represents the rate of change of power system frequency, T PV is the time constant of the PV inverter, and s represents the differential operator.

[0025] In another aspect of the present invention, preferably, the load demand includes load power fluctuation, and the power system frequency deviation is calculated by the following formula:

[0026]

[0027] Where Δf represents the power system frequency deviation, ΔP WF is the output power change of the wind turbine, ΔP PV is the output power change of the photovoltaic unit, ΔP TP is the output power change of the thermal power unit; ΔP L is the power fluctuation of the load; M and D are the inertia time constant and damping coefficient of the power system respectively. Indicates the rate of change of power system frequency.

[0028] In another aspect of the present invention, preferably, the objective function is expressed as:

[0029]

[0030] Among them, P ref is the output power reference value of the new energy power supply; P i is the actual output value of the new energy power source at time i; P ref,i is the reference value of the frequency controller output power of the new energy power source at time i, t0+t s Indicates a time interval.

[0031] In another aspect of the present invention, preferably,

[0032] The observed variables of the objective function are:

[0033] [Δf,ΔP TP ,ΔP WF ,ΔP PV ]

[0034] The frequency controller model parameters of the new energy power supply are:

[0035]

[0036] Where Δf represents the power system frequency deviation, ΔP WF is the output power change of the wind turbine, ΔP PV is the output power change of the photovoltaic unit, ΔP TP is the output power change of the thermal power unit, are the inertia control coefficient and droop control coefficient of the wind turbine frequency controller, They are the inertia control coefficient and droop control coefficient of the PV unit frequency controller respectively.

[0037] Another aspect of the present invention preferably further includes setting a frequency modulation energy efficiency evaluation index of the new energy power source, and using the frequency modulation energy efficiency and frequency modulation contribution of the new energy source to evaluate the frequency modulation energy efficiency.

[0038] In another aspect of the present invention, preferably,

[0039] The frequency modulation energy efficiency evaluation index of the new energy power source is expressed as:

[0040]

[0041] Where W represents the frequency modulation energy efficiency evaluation index of the new energy power source; t0 represents the time of the first frequency modulation action of the new energy power source; t s is the adjustment time of the primary frequency regulation of the new energy power source; P represents the output of the new energy power source during the primary frequency regulation process; P0 represents the active output of the new energy power source before the primary frequency regulation action.

[0042] In another aspect of the present invention, preferably, a new energy frequency modulation energy efficiency improvement system based on frequency controller parameter optimization includes:

[0043] The first establishment module is to establish a frequency response model for each type of new energy power source, wherein the frequency response model is established based on the unit model of the new energy power source and the frequency controller model of the new energy power source;

[0044] The first calculation module calculates the power system frequency deviation based on the output power change of the new energy power source, the output power change of the traditional power source and the load demand;

[0045] A second calculation module: calculating a reference value of an output power variation of the new energy power source based on the frequency response model;

[0046] The third calculation module is used to calculate the output power reference value of the new energy power source according to the output power change reference value of the new energy power source;

[0047] The second establishment module: establishes the objective function of energy efficiency optimization of new energy frequency regulation based on the difference between the output power reference value and the actual output of the new energy power source;

[0048] Optimization module: solves the objective function through particle swarm algorithm and optimizes the frequency controller model parameters of the new energy power supply.

[0049] (3) Beneficial effects

[0050] The above technical solution of the present invention has the following beneficial technical effects:

[0051] The present invention establishes frequency response models of new energy power sources and traditional power sources, accurately calculates the reference value of the output power variation of each power source, and uses a particle swarm algorithm to optimize the parameters of the new energy frequency controller, overcoming the limitations of traditional empirical tuning methods. The optimized parameters are used for control, thereby improving the energy efficiency of new energy frequency modulation and the frequency control effect of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 is an overall flow chart of an embodiment of the present invention;

[0053] Figure 2 is a schematic diagram of the frequency response of a power system according to an embodiment of the invention;

[0054] Figure 3 This is a comparison chart of the frequency modulation energy efficiency improvement effect of an embodiment of the invention;

[0055] Figure 4 This is a comparison diagram of the frequency modulation output of a wind turbine generator set according to an embodiment of the invention;

[0056] Figure 5 This is a comparison chart of the frequency modulation output of a photovoltaic unit according to an embodiment of the invention. DETAILED DESCRIPTION

[0057] To make the objectives, technical solutions, and advantages of the present invention more clearly understood, the present invention will be further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings. It should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present invention. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present invention.

[0058] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0059] In the description of the present invention, it should be noted that the terms "first", "second" and "third" are only used for descriptive purposes and should not be understood as indicating or implying relative importance.

[0060] In addition, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0061] The present invention will be described in more detail below with reference to the accompanying drawings. In each of the accompanying drawings, identical elements are represented by similar reference numerals. For the sake of clarity, the various parts in the accompanying drawings are not drawn to scale.

[0062] Example 1

[0063] A new energy frequency modulation energy efficiency improvement method based on frequency controller parameter optimization, Figure 1 FIG. 1 shows an overall flow chart of an embodiment of the present invention, as shown in FIG. Figure 1 Shown, including:

[0064] A frequency response model for each type of new energy power source is established respectively, and the frequency response model is established based on the unit model and frequency controller model of the power source; the frequency response model of each type of new energy power source is used to calculate the reference value of the output power change; the frequency response model of each type of new energy power source is established based on the unit model of each type of new energy power source and its corresponding frequency controller model. The unit model describes the relationship between the unit output power and the frequency control instruction, and simulates the dynamic response of the inverter through the first-order inertia link. The frequency controller model includes inertia control and droop control, which respond to the frequency change rate and frequency deviation respectively. The frequency response model combines the unit model with the controller to form a closed-loop control. In this embodiment, the types of new energy power sources include wind turbines and photovoltaic units.

[0065] Calculating a reference value of an output power variation of a new energy power source and a reference value of an output power variation of a traditional power source based on the frequency response model; Figure 2 FIG. 1 shows a schematic diagram of a power system frequency response according to an embodiment of the present invention. Figure 2 As shown, in this embodiment, the wind turbine model is calculated using the following formula:

[0066]

[0067] The wind turbine frequency controller model is calculated using the following formula:

[0068]

[0069] Based on the wind turbine model and wind turbine frequency controller model, the frequency response model of the wind turbine is established and calculated using the following formula:

[0070]

[0071] in, is the reference value of the output power variation of the wind turbine; are the inertia control coefficient and droop control coefficient of the wind turbine frequency controller, respectively, and Δf is the power system frequency deviation; represents the rate of change of power system frequency, T WF is the time constant of the wind turbine inverter, and s represents the differential operator.

[0072] Furthermore, in this embodiment, the unit model of the photovoltaic unit is calculated using the following formula:

[0073]

[0074] The PV unit frequency controller model is calculated using the following formula:

[0075]

[0076] Based on the PV unit model and PV unit frequency controller model, the frequency response model of the PV unit is established and calculated using the following formula:

[0077]

[0078] in, is the reference value of the output power variation of the photovoltaic unit; are the inertia control coefficient and droop control coefficient of the PV unit frequency controller respectively; Δf is the power system frequency deviation; represents the rate of change of power system frequency, T PV is the time constant of the PV inverter, and s represents the differential operator.

[0079] The power system frequency deviation is calculated based on the output power variation of the new energy power source, the output power variation of the traditional power source, and the load demand. In this embodiment, the load demand includes the power fluctuation of the load. The power system frequency deviation is calculated using the following formula:

[0080]

[0081] Where Δf represents the power system frequency deviation, ΔP WF is the output power change of the wind turbine, ΔP PV is the output power change of the photovoltaic unit, ΔP TP is the output power change of the thermal power unit; ΔP L is the power fluctuation of the load; M and D are the inertia time constant and damping coefficient of the power system respectively. Indicates the rate of change of power system frequency.

[0082] Calculate the output power reference value of the new energy power source based on the output power variation reference value of the new energy power source; the output power reference value of the new energy power source is obtained by adding the output P0 before the new energy frequency regulation action to the output power variation reference value of the new energy power source;

[0083] Based on the difference between the output power reference value and the actual output of the new energy power source, an objective function for optimizing the frequency modulation energy efficiency of the new energy power source is established. The objective function is to minimize the integral value of the absolute value of the difference between the output power reference value and the actual output of the frequency controller during the primary frequency modulation process of the new energy power source. The objective function is calculated using the following formula:

[0084]

[0085] Among them, P ref is the output power reference value of the new energy power supply; P i is the actual output value of the new energy power source at time i; P ref,iis the reference value of the frequency controller output power of the new energy power source at time i, t0+t s Indicates a time interval;

[0086] The observed variables are represented by real-time dynamic parameters input to the optimization model. The observed variables are the frequency of the power system and the output of traditional power sources and new energy power sources. In this embodiment, the observed variables are:

[0087] [Δf,ΔP TP ,ΔP WF ,ΔP PV ]

[0088] The frequency controller model parameters of the new energy power supply are adjustable control parameters in the optimization model, which are the virtual inertia control coefficient and virtual droop coefficient of the frequency controller of the new energy power supply. In this embodiment, the frequency controller model parameters of the new energy power supply are:

[0089]

[0090] Where Δf represents the power system frequency deviation, ΔP WF is the output power change of the wind turbine, ΔP PV is the output power change of the photovoltaic unit, ΔP TP is the output power change of the thermal power unit, are the inertia control coefficient and droop control coefficient of the wind turbine frequency controller, They are the inertia control coefficient and droop control coefficient of the PV unit frequency controller respectively.

[0091] The objective function is solved by particle swarm algorithm to optimize the frequency controller model parameters of the new energy power supply. The particle swarm algorithm is used to optimize the decision variables and improve the energy efficiency of the new energy frequency regulation by minimizing the integral value of the absolute value of the difference between the reference value and the actual output of the frequency controller during the primary frequency regulation of the new energy power supply. best and the optimal position G among all particles best To iterate, the expressions for updating the speed and position of the i-th particle are as follows:

[0092] v i =ωv i +c1×rand(0,1)(P best,i -x i )+c2×rand(0,1)(G best,i -x i )

[0093] x i =xi +v i

[0094] Where, v i is the velocity of the particle; x i is the current position of the particle; c1 and c2 are learning factors; ω is the inertia factor; rand(0,1) is a random number between (0,1).

[0095] The particle swarm algorithm calculates the fitness of the particle before and after the update and compares them. If the fitness is better, the particle's optimal position is updated; if the fitness of the particle's optimal position is higher than the particle swarm's optimal fitness value, the optimal position of all particles is updated. The specific steps of the particle swarm algorithm are as follows:

[0096] (1) Initialization of particle swarm algorithm parameters;

[0097] (2) Calculate the fitness value of the particles and save the optimal position of each particle and the best position of the population;

[0098] (3) Update speed and position;

[0099] (4) Recalculate the updated particle fitness value. If it is good, update the optimal position of each particle.

[0100] (5) Compare the optimal position of the particle with the best position of the population. If it is better, update the best position of the population.

[0101] (6) Determine whether the stopping condition is met. If so, output the optimal value; otherwise, go to step (3).

[0102] The particle swarm algorithm optimizes the parameters of the frequency controller of the new energy unit by observing the frequency of the system and the output of traditional power sources and new energy power sources in the system, thereby improving the frequency regulation efficiency and contribution of the new energy unit.

[0103] Furthermore, in this embodiment, a frequency modulation energy efficiency evaluation index of a new energy source is set, and the frequency modulation energy efficiency and frequency modulation contribution of the new energy source are evaluated based on the frequency modulation energy efficiency evaluation index. The frequency modulation energy efficiency evaluation index of the new energy source is calculated using the following formula:

[0104]

[0105] Where W represents the frequency modulation energy efficiency evaluation index of the new energy power source; t0 represents the time of the first frequency modulation action of the new energy power source; t s The frequency modulation time of the new energy source is regulated; P represents the output of the new energy source during the frequency modulation process; and P0 represents the active power output of the new energy source before the frequency modulation begins. The energy contributed by the new energy source during the frequency modulation process reflects the frequency modulation efficiency and contribution of the new energy source.

[0106] Figure 3 A comparison diagram showing the frequency modulation energy efficiency improvement effect of an embodiment of the present invention is shown; Figure 4 A comparison diagram of frequency modulation output of a wind turbine generator system according to an embodiment of the present invention is shown; Figure 5 FIG1 shows a comparison diagram of the frequency modulation output of a photovoltaic unit according to an embodiment of the present invention. Figure 3 、 Figure 4 and Figure 5 As shown in the figure, PID represents traditional parameter control, PSO represents particle swarm algorithm optimized parameter control, and when the parameters optimized by this embodiment are used for control, the frequency fluctuation is smaller than the fluctuation of the parameters before optimization.

[0107] The present invention establishes frequency response models of new energy power sources and traditional power sources, accurately calculates the reference value of the output power variation of each power source, and uses a particle swarm algorithm to optimize the parameters of the new energy frequency controller, overcoming the limitations of traditional empirical tuning methods. The optimized parameters are used for control, thereby improving the energy efficiency of new energy frequency modulation and the frequency control effect of the power system.

[0108] Example 2

[0109] A new energy frequency modulation energy efficiency improvement system based on frequency controller parameter optimization, comprising:

[0110] The first establishment module is to establish a frequency response model for each type of new energy power source, wherein the frequency response model is established based on the unit model of the new energy power source and the frequency controller model of the new energy power source;

[0111] The first calculation module calculates the power system frequency deviation based on the output power change of the new energy power source, the output power change of the traditional power source and the load demand;

[0112] A second calculation module: calculating a reference value of an output power variation of the new energy power source based on the frequency response model;

[0113] The third calculation module is used to calculate the output power reference value of the new energy power source according to the output power change reference value of the new energy power source;

[0114] The second establishment module: establishes the objective function of energy efficiency optimization of new energy frequency regulation based on the difference between the output power reference value and the actual output of the new energy power source;

[0115] Optimization module: solves the objective function through particle swarm algorithm and optimizes the frequency controller model parameters of the new energy power supply.

[0116] It should be understood that the above-described specific embodiments of the present invention are merely illustrative or illustrative of the principles of the present invention and do not constitute limitations of the present invention. Therefore, any modifications, equivalent substitutions, improvements, etc. made without departing from the spirit and scope of the present invention should be included within the scope of protection of the present invention. In addition, the appended claims are intended to cover all variations and modifications that fall within the scope and metes and bounds of the appended claims, or equivalents thereof.

[0117] The present invention has been described above with reference to the embodiments thereof. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present invention. The scope of the present invention is defined by the appended claims and their equivalents. Those skilled in the art may make various substitutions and modifications without departing from the scope of the present invention, and such substitutions and modifications are intended to fall within the scope of the present invention.

[0118] Although the embodiments of the present invention have been described in detail, it should be understood that the various changes, substitutions, and alterations could be made hereto without departing from the spirit and scope of the invention.

[0119] Obviously, the above embodiments are merely examples for clarity of explanation and are not intended to limit the implementation methods. Those skilled in the art will readily appreciate that other variations or modifications based on the above descriptions are possible. It is not necessary and impossible to enumerate all implementation methods here. Obvious variations or modifications arising therefrom remain within the scope of protection of the present invention.

Claims

1. A method for improving energy efficiency of new energy frequency modulation based on frequency controller parameter optimization, characterized in that: include: Establishing frequency response models for each type of new energy power source, respectively, wherein the frequency response models are established based on a unit model of the new energy power source and a frequency controller model of the new energy power source; Calculate the power system frequency deviation based on the output power change of new energy power sources, the output power change of traditional power sources and load demand; Calculating a reference value of output power variation of the new energy power source based on the frequency response model; Calculate the output power reference value of the new energy power source according to the output power variation reference value of the new energy power source; According to the difference between the output power reference value and the actual output of the new energy power source, the objective function of the new energy frequency regulation energy efficiency optimization is established; The objective function is solved by particle swarm optimization to optimize the frequency controller model parameters of the new energy power supply.

2. The method for improving energy efficiency of new energy frequency modulation based on frequency controller parameter optimization according to claim 1 is characterized in that: The unit model represents the relationship between the unit output power and the frequency control command, and simulates the dynamic response of the inverter through the first-order inertia link; The frequency controller model includes inertia control and droop control.

3. The method for improving energy efficiency of new energy frequency modulation based on frequency controller parameter optimization according to claim 1 is characterized in that: The new energy power source includes a wind turbine; The frequency response model of the wind turbine generator system is expressed as: in, is the reference value of the output power variation of the wind turbine; are the inertia control coefficient and droop control coefficient of the wind turbine frequency controller, respectively, and Δf is the power system frequency deviation; represents the rate of change of power system frequency, T WF is the time constant of the wind turbine inverter, and s represents the differential operator.

4. The method for improving energy efficiency of new energy frequency modulation based on frequency controller parameter optimization according to claim 1 is characterized in that: The new energy power source includes a photovoltaic unit; The frequency response model of the photovoltaic system is expressed as: in, is the reference value of the output power variation of the photovoltaic unit; are the inertia control coefficient and droop control coefficient of the PV unit frequency controller respectively; Δf is the power system frequency deviation; represents the rate of change of power system frequency, T PV is the time constant of the PV inverter, and s represents the differential operator.

5. The method for improving energy efficiency of new energy frequency modulation based on frequency controller parameter optimization according to claim 1 is characterized in that: The load demand includes the power fluctuation of the load, and the power system frequency deviation is calculated by the following formula: Where Δf represents the power system frequency deviation, ΔP WF is the output power change of the wind turbine, ΔP PV is the output power change of the photovoltaic unit, ΔP TP is the output power change of the thermal power unit; ΔP L is the power fluctuation of the load; M and D are the inertia time constant and damping coefficient of the power system respectively. Indicates the rate of change of power system frequency.

6. The method for improving energy efficiency of new energy frequency modulation based on frequency controller parameter optimization according to claim 1 is characterized in that: The objective function is expressed as: Among them, P ref is the output power reference value of the new energy power supply; P i is the actual output value of the new energy power source at time i; P ref,i is the reference value of the frequency controller output power of the new energy power source at time i, t0+t s Indicates a time interval.

7. The method for improving energy efficiency of new energy frequency modulation based on frequency controller parameter optimization according to claim 6 is characterized in that: The observed variables of the objective function are: [Δf,ΔP TP ,ΔP WF ,ΔP PV ] The frequency controller model parameters of the new energy power supply are: Where Δf represents the power system frequency deviation, ΔP WF is the output power change of the wind turbine, ΔP PV is the output power change of the photovoltaic unit, ΔP TP is the output power change of the thermal power unit, are the inertia control coefficient and droop control coefficient of the wind turbine frequency controller, They are the inertia control coefficient and droop control coefficient of the PV unit frequency controller respectively.

8. The method for improving energy efficiency of new energy frequency modulation based on frequency controller parameter optimization according to claim 1, characterized in that: It also includes setting a frequency modulation energy efficiency evaluation index for the new energy power source, and using the frequency modulation energy efficiency evaluation index to evaluate the frequency modulation energy efficiency and frequency modulation contribution of the new energy source.

9. The method for improving energy efficiency of new energy frequency modulation based on frequency controller parameter optimization according to claim 8, characterized in that: The frequency modulation energy efficiency evaluation index of the new energy power source is expressed as: Where W represents the frequency modulation energy efficiency evaluation index of the new energy power source; t0 represents the time of the first frequency modulation action of the new energy power source; t s is the adjustment time of the primary frequency regulation of the new energy power source; P represents the output of the new energy power source during the primary frequency regulation process; P0 represents the active output of the new energy power source before the primary frequency regulation action.

10. A new energy frequency modulation energy efficiency improvement system based on frequency controller parameter optimization, characterized in that: include: The first establishment module is to establish a frequency response model for each type of new energy power source, wherein the frequency response model is established based on the unit model of the new energy power source and the frequency controller model of the new energy power source; The first calculation module calculates the power system frequency deviation based on the output power change of the new energy power source, the output power change of the traditional power source and the load demand; A second calculation module: calculating a reference value of an output power variation of the new energy power source based on the frequency response model; The third calculation module is used to calculate the output power reference value of the new energy power source according to the output power change reference value of the new energy power source; The second establishment module: establishes the objective function of energy efficiency optimization of new energy frequency regulation based on the difference between the output power reference value and the actual output of the new energy power source; Optimization module: solves the objective function through particle swarm algorithm and optimizes the frequency controller model parameters of the new energy power supply.

Images